Discovering complex associations, anomalies and patterns in distributed data sets is gaining popularity in a range of scientific, medical and business applications. Various algor...
Omer F. Rana, David W. Walker, Maozhen Li, Steven ...
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the...
There has been increasing interest in the problem of building accurate data mining models over aggregate data, while protecting privacy at the level of individual records. One app...
Alexandre V. Evfimievski, Johannes Gehrke, Ramakri...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...